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Related Concept Videos

Transformers01:26

Transformers

1.1K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
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The Ideal Transformer01:26

The Ideal Transformer

449
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
449
Types Of Transformers01:16

Types Of Transformers

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Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
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Transformers in Distribution System01:27

Transformers in Distribution System

134
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Source Transformation01:15

Source Transformation

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Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that when...
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Chat Generative Pre-trained Transformer: why we should embrace this technology.

Martin R Chavez1, Thomas S Butler2, Patricia Rekawek1

  • 1Division of Maternal-Fetal Medicine, Department of Obstetrics Gynecology, New York University Langone Hospital-Long Island, New York University Long Island School of Medicine, Mineola, NY.

American Journal of Obstetrics and Gynecology
|March 16, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI), like Chat Generative Pre-trained Transformer, offers new communication possibilities in medicine. Clinicians should actively guide AI development for optimal integration into medical practice.

Keywords:
Chat Generative Pre-trained TransformerOpenAIartificial intelligencefuture of medicinelarge language modelsplain conversational language interfaces

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Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Clinical Practice

Background:

  • The increasing sophistication of AI enables human-like communication.
  • Widespread human-AI interaction is becoming a reality.
  • AI tools are emerging with potential applications in healthcare.

Purpose of the Study:

  • To explore the potential uses of Chat Generative Pre-trained Transformer (CGPT) in obstetrics and gynecology.
  • To encourage clinicians to actively participate in shaping AI's role in medicine.

Main Methods:

  • This is a clinical opinion piece.
  • It discusses the potential applications of CGPT for obstetrician-gynecologists.
  • It emphasizes the importance of understanding AI's capabilities and limitations.

Main Results:

  • CGPT presents significant potential for use in medical practice.
  • Understanding AI's power and limitations is key to its effective utilization.
  • Clinician involvement is crucial for maximizing AI's benefits.

Conclusions:

  • Obstetrician-gynecologists can benefit from understanding and utilizing CGPT.
  • Active engagement by clinicians is vital for the responsible development of AI in medicine.
  • AI tools like CGPT represent a new frontier in medical practice.